Abstract: The present disclosure involves systems, software, and computer implemented methods for an artificial intelligence work center for ERP data. One example method includes receiving scenario and model settings for an artificial intelligence model for a predictive scenario. A copy of the dataset is processed based on settings to generate a prepared dataset that is provided with the settings to a predictive analytical library. A trained model trained and evaluation data for the trained model is received from the predictive analytical library. A request is received to generate a prediction for the predictive scenario for a target field for a record of the dataset. The record of the dataset is provided to the trained model and a prediction for the target field for the record the dataset is received from the model. The prediction is included for presentation in a user interface that displays information from the dataset.

Abstract: An engine exhaust aftertreatment component includes a housing defining an exhaust flow path from an exhaust inlet to an exhaust outlet. The housing supports an internal support channel. An aftertreatment brick module includes a catalytic brick, a can configured to receive the catalytic brick, and an end plate disposed along an end of the can. The end plate includes a coupling mechanism configured to be received within the internal support channel.

Abstract: An engine exhaust aftertreatment component includes a housing defining an exhaust flow path from an exhaust inlet to an exhaust outlet. The housing supports an internal support channel. An aftertreatment brick module includes a catalytic brick, a can configured to receive the catalytic brick, and an end plate disposed along an end of the can. The end plate includes a coupling mechanism configured to be received within the internal support channel.